diff options
| author | Chayan Bhawal | 2018-10-02 17:16:28 +0530 |
|---|---|---|
| committer | Chayan Bhawal | 2018-10-02 17:16:28 +0530 |
| commit | fc216fe63a386754a1cbc905e2599b780fb1b911 (patch) | |
| tree | e93744ba1f5b038252743cbce6eb1a1afa31eb31 | |
| parent | 3d0c890de4ac7d9afd576e889bd2624437d79c70 (diff) | |
| download | scilab-tutorials-fc216fe63a386754a1cbc905e2599b780fb1b911.tar.gz scilab-tutorials-fc216fe63a386754a1cbc905e2599b780fb1b911.tar.bz2 scilab-tutorials-fc216fe63a386754a1cbc905e2599b780fb1b911.zip | |
Curve_fit_code_plot
| -rw-r--r-- | Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting.sce | 7 | ||||
| -rw-r--r-- | Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting_weighted.sce | 10 |
2 files changed, 11 insertions, 6 deletions
diff --git a/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting.sce b/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting.sce index 3dc7e27..a289ca3 100644 --- a/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting.sce +++ b/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting.sce @@ -27,7 +27,10 @@ disp(error,'The error after least square approximation') // Plot of measured data and fitted data versus time -fitted_data = fit_function(time, coeff_optimal); -plot2d(time, [measured_data,fitted_data], [-1,2]) +// a small graphic +fit_time = 0:0.01:15; +fitted_data = fit_function(fit_time, coeff_optimal); +plot2d(time, measured_data, -1) +plot2d(fit_time, fitted_data, 2) legend(["measure points", "fitted curve"],[-1,2],"ur"); xtitle("a simple fit with leastsq","time","data") diff --git a/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting_weighted.sce b/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting_weighted.sce index 39973bc..ad85818 100644 --- a/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting_weighted.sce +++ b/Tutorial03-Curve_fitting/Scilab_code/Tutorial3_curve_fitting_weighted.sce @@ -24,14 +24,16 @@ weight_matrix = [1 1 1 1 1 1 5 5 5 5 5 5 5]'; initial_condition = [1 ; 1]; //f is the function value at optimal x (xopt) -[func_value_xopt,x_optimal] = leastsq(list(errorfunweight,time,measured_data,weight_matrix),initial_condition) +[func_value_xopt,coeff_optimal] = leastsq(list(errorfunweight,time,measured_data,weight_matrix),initial_condition) -error = errorfunweight(x_optimal,time,measured_data,weight_matrix) +error = errorfunweight(coeff_optimal,time,measured_data,weight_matrix) disp(error,'The error after least square approximation') // a small graphic -fitted_data = fit_function(time, x_optimal); -plot2d(time, [measured_data,fitted_data], [-1,2]) +fit_time = 0:0.01:15; +fitted_data = fit_function(fit_time, coeff_optimal); +plot2d(time, measured_data, -1) +plot2d(fit_time, fitted_data, 2) legend(["measure points", "fitted curve"],[-1,2],"ur"); xtitle("a simple fit with leastsq","time","data") |